An unfortunate reality of trying to represent continuous real numbers in a fixed space (e.g. with a limited number of bits) is that this comes with an inevitable loss of both precision and accuracy.
AI/ML training traditionally has been performed using floating point data formats, primarily because that is what was available. But this usually isn’t a viable option for inference on the edge, where ...
AI is all about data, and the representation of the data matters strongly. But after focusing primarily on 8-bit integers and 32‑bit floating-point numbers, the industry is now looking at new formats.
If you are used to writing software for modern machines, you probably don’t think much about computing something like one divided by three. Modern computers handle floating point quite well. However, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results